TY - JOUR
T1 - Order filtering neural network
AU - Chen, Chi Ming
AU - Yang, Jar Ferr
N1 - Funding Information:
The research was supported by National Science Council under contract # NSC 84-2213-E-006-079, Taiwan, ROC.
PY - 1996
Y1 - 1996
N2 - In this paper, a simple order filtering neural network, which can progressively output the value of a specific ordered input, is proposed. The progressive order filtering neural network (POFNN) is developed in a simple two-layer structure embedded with robustness. Both theoretical analyses and simulated results show that the designed order filtering neural network converges to the solution in logarithmic function of the dynamic range and the accuracy threshold, which are independent of the number of inputs.
AB - In this paper, a simple order filtering neural network, which can progressively output the value of a specific ordered input, is proposed. The progressive order filtering neural network (POFNN) is developed in a simple two-layer structure embedded with robustness. Both theoretical analyses and simulated results show that the designed order filtering neural network converges to the solution in logarithmic function of the dynamic range and the accuracy threshold, which are independent of the number of inputs.
UR - https://www.scopus.com/pages/publications/0030103798
UR - https://www.scopus.com/pages/publications/0030103798#tab=citedBy
U2 - 10.1080/02533839.1996.9677786
DO - 10.1080/02533839.1996.9677786
M3 - Article
AN - SCOPUS:0030103798
SN - 0253-3839
VL - 19
SP - 265
EP - 271
JO - Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an
JF - Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an
IS - 2
ER -